Focal cortical dysplasia lesion segmentation using multiscale transformer.

ABSTRACT:

Objectives

Accurate segmentation of focal cortical dysplasia (FCD) lesions from MR images plays an important role in surgical planning and decision but is still challenging for radiologists and clinicians. In this study, we introduce a novel transformer-based model, designed for the end-to-end segmentation of FCD lesions from multi-channel MR images.

Methods

The core innovation of our proposed model is the integration of a convolutional neural network-based encoder-decoder structure with a multiscale transformer to augment the feature representation of lesions in the global field of view. Transformer pathways, composed of memory- and computation-efficient dual-self-attention modules, leverage feature maps from varying depths of the encoder to discern long-range interdependen

SUBMITTER: Zhang X 

PROVIDER: S-EPMC11393231 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature